Collusion attack is a malicious watermark removal attack in which the hacker has access to multiple copies of the
same content with different watermarks and tries to remove the watermark using averaging. In the literature, several
solutions to collusion attacks have been reported. The main stream solutions aim at designing watermark codes
that are inherently resistant to collusion attacks. The other approaches propose signal processing based solutions
that aim at modifying the watermarked signals in such a way that averaging multiple copies of the content leads
to a significant degradation of the content quality. In this paper, we present signal processing based technique
that may be deployed for deterring collusion attacks. We formulate the problem in the context of electronic music
distribution where the content is generally available in the compressed domain. Thus, we first extend the collusion
resistance principles to bit stream signals and secondly present experimental based analysis to estimate a bound on
the maximum number of modified versions of a content that satisfy good perceptibility requirement on one hand
and destructive averaging property on the other hand.
One of the important stages of fingerprint recognition is the registration of the fingerprints with respect to the original template. This is not a straightforward task as fingerprint images may have been subject to rotations and translations. Popular
techniques for fingerprint registration use a reference point to achieve alignment. The drawback of existing methods of
core/reference point detection is their poor performance on rotated images. In this paper, we propose a new approach for
rotation invariant and reliable reference point detection applicable to fingerprints of different quality and types. Our approach
is based on the integration of a directional vector field (representing the doubled ridge orientations in fingerprints)
over a closed contour. We define the reference point as the point of the highest curvature. Areas of high curvature in the fingerprint are characterized by large differences in the orientations and correspond to high curvatures in the directional vector fields. Closed contour integrals of orientation vector field, defined as above, over a circle centered around the reference point corresponds to maximal closed curve integrals, and the values associated with such integrals are rotation invariant. Experimental results prove that with the proposed approach we can locate the reference point with high accuracy. Comparison with existing methods is provided.
Successful watermarking algorithms have already been developed for various applications ranging from meta-data tagging to forensic tracking. Nevertheless, it is commendable to develop alternative watermarking techniques that provide a broader basis for meeting emerging services, usage models and security threats. To this end, we propose a new multiplicative watermarking technique for video, which is based on the principles of our successful MASK audio watermark. Audio-MASK has embedded the watermark by modulating the short-time envelope of the audio signal and performed detection using a simple envelope detector followed by a SPOMF (symmetrical phase-only matched filter). Video-MASK takes a similar approach and modulates the image luminance envelope. In addition, it incorporates a simple model to account for the luminance sensitivity of the HVS (human visual system). Preliminary tests show algorithms transparency and robustness to lossy compression.
In recent literature, privacy protection technologies for biometric templates were proposed. Among these is the so-called helper-data system (HDS) based on reliable component selection. In this paper we integrate this approach with face biometrics such that we achieve a system in which the templates are privacy protected, and multiple templates can be derived from the same facial image for the purpose of template renewability. Extracting binary feature vectors forms an essential step in this process. Using the FERET and Caltech databases, we show that this quantization step does not significantly degrade the classification performance compared to, for example, traditional correlation-based classifiers. The binary feature vectors are integrated in the HDS leading to a privacy protected facial recognition algorithm with acceptable FAR and FRR, provided that the intra-class variation is sufficiently small. This suggests that a controlled enrollment procedure with a sufficient number of enrollment measurements is required.
In recent years we have seen many initiatives to provide electronic music delivery (EMD) services. We observe that a key success factor in EMD is the transparency of the distribution service. We could compare it with the traditional music distribution via compact discs. By buying a CD, a user acquires a 'free' control of the content, i.e. he can copy it, he can play it multiple times etc. In the electronic equivalent, the usage and digital rights management rules should be transparent, and preferably comparable to the classical method of distributing contents.
It is the goal of this paper to describe a technology concept that facilitates, from a consumer perspective simple EMD service. Digital watermarking and fingerprinting are the two key technologies involved. The watermarking technology is used to convey the information that uniquely identifies a specific transaction, and the fingerprint technology is adopted for key management and security purposes. In this paper, we discuss how these two technologies are integrated in such a way that watermark security (i.e. the inability to maliciously alter the watermark) and distribution efficiency (i.e. the ability to serve multiple consumers with one distribution PC) are maximized.
Reversible watermarking is a technique for embedding data in a digital host signal
in such a manner that the original host signal can be restored in a bit-exact
manner in the restoration process. In this paper, we present a general framework
for reversible watermarking in multi-media signals. A mapping function, which
is in general neither injective nor surjective, is used to map the input signal
to a perceptually equivalent output signal. The resulting unused sample values of
the output signal are used to encode additional (watermark) information and
At the 2003 SPIE conference, examples of this technique applied to digital audio
were presented. In this paper we concentrate on color and gray-scale images.
A particular challenge in this context is not only the optimization of rate-distortion,
but also the measure of perceptual quality (i.e. the distortion). In literature
distortion is often expressed in terms of PSNR, making comparison among different
techniques relatively straightforward. We show that our general framework for
reversible watermarking applies to digital images and that results can be presented
in terms of PSNR rate-distortions. However, the framework allows for more subtle
signal manipulations that are not easily expressed in terms of PSNR distortion.
These changes involve manipulations of contrast and/or saturation.
A digital watermark can be seen as an information channel, which is hidden in a cover signal. It is usually designed to be imperceptible to human observers. Although imperceptibility is often achieved, the inherent modification of the cover signal may be viewed as a potential disadvantage. In this paper, we present a reversible watermarking technique for digital audio signals. In our context reversibility refers to the ability to restore the original input signal in the watermark detector. In summary, the approach works as follows. In the encoder, the dynamic range of the input signal is limited (i.e. it is compressed), and part of the unused bits is deployed for encoding the watermark bits. Another part of these bits is used to convey information for the bit-exact reconstruction of the cover signal. It is the purpose of the watermark detector to extract the watermark and reconstruct the input signal by restoring the original dynamic range. In this study we extensively tested this new algorithm with a variety of settings using audio items with different characteristics. These experiments showed that for 16bit PCM audio, capacities close to 1-bit per sample can be achieved, while perceptual degradation of the watermarked signal remained acceptable.